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As a Product Data Scientist, you'll sit at the heart of product decision-making, solving complex challenges and shaping experiences for millions of users. This isn’t a role for someone looking to coast — it's for someone who thrives in ambiguity, embraces experimentation, and craves the thrill of seeing their work drive real-world outcomes.
You'll work closely with product, design, and engineering to optimize user journeys, personalize recommendations, and build the systems that power insight-driven growth. From day one, you’ll be trusted to own high-impact projects and ship data science products that make a difference.
What You’ll Do
- Model Intelligence into Product: Build and deploy machine learning models that tackle critical product problems — from recommendation engines and segmentation models to churn predictors — and partner with ML Engineers to bring them to production.
- Advance Product Understanding: Apply causal inference methods and advanced experimental design to evaluate product initiatives, ensuring every decision is grounded in robust data.
- Own Data Infrastructure: Develop scalable data models and pipelines that fuel analytics, experimentation, and personalization at scale.
- Collaborate at Speed: Work hand-in-hand with cross-functional stakeholders to translate evolving business needs into actionable data science solutions.
- Influence Roadmaps with Insight: Provide clear, data-backed product insights and uncover opportunities that drive user engagement and retention.
- Understand & Predict Behavior: Build behavioral models that power adaptive user experiences and surface key signals for product teams.
- Advanced degree (MSc/PhD) in a quantitative field like Data Science, Computer Science, Statistics, or Applied Math.
- 3+ years of experience in a fast-paced, product-focused data science role.
- Expertise in at least one of the following: recommendation systems, causal inference (e.g., uplift modeling), segmentation, or churn prediction.
- Strong knowledge of experimental methods (A/B tests, quasi-experiments) and causal inference.
- Proficiency in Python and libraries such as pandas, scikit-learn, PyTorch, TensorFlow, or XGBoost.
- Skilled in SQL and data wrangling across large datasets.
- Experience with cloud-based data platforms (AWS, GCP, or Azure).
- Excellent communication skills — able to influence non-technical stakeholders and translate findings into action.
- A bias toward action: comfortable building in ambiguity and learning on the fly.
High Pace. High Growth. Real Impact.
We’re building a place where data scientists can thrive — not by sitting on the sidelines, but by being embedded in the action. At Patrianna, your work won’t sit in dashboards. It will launch in real products, shift real metrics, and shape the way millions of people experience our platform. If you're ready to move fast, learn relentlessly, and own your impact — we want to hear from you.
Key Skills
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